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Abstract The reverse flat-plate collector is a non-concentrating collector. It can collect solar heat at high temperatures which cannot be achieved by conventional non-concentrating collectors. In this paper, the authors have proposed a number of modified versions of the originally proposed reverse flat-plate collector. The new designs are of single, as well as double, absorber type. The thermal performance of these modified reverse flat-plate collectors is compared with that of a single absorber reverse flat-plate collector, as well as with the corresponding normal flat-plate collector. It is found that the new design having two absorbers gives the best thermal performance as compared with other configurations. The analytical models presented in this paper very well describe the experimental results.

Abstract The reverse flat-plate collector is a non-concentrating collector. It can collect solar heat at high temperatures which cannot be achieved by conventional non-concentrating collectors. In this paper, the authors have proposed a number of modified versions of the originally proposed reverse flat-plate collector. The new designs are of single, as well as double, absorber type. The thermal performance of these modified reverse flat-plate collectors is compared with that of a single absorber reverse flat-plate collector, as well as with the corresponding normal flat-plate collector. It is found that the new design having two absorbers gives the best thermal performance as compared with other configurations. The analytical models presented in this paper very well describe the experimental results.

Drying experiments have been performed with potato cylinders and slices using a laboratory scale designed natural convection mixed-mode solar dryer. The drying data were fitted to eight different mathematical models to predict the drying kinetics, and the validity of these models were evaluated statistically through coefficient of determination (R(2)), root mean square error (RMSE) and reduced chi-square (χ (2)). The present investigation showed that amongst all the mathematical models studied, the Modified Page model was in good agreement with the experimental drying data for both potato cylinders and slices. A mathematical framework has been proposed to estimate the performance of the food dryer in terms of net CO2 emissions mitigation potential along with unit cost of CO2 mitigation arising because of replacement of different fossil fuels by renewable solar energy. For each fossil fuel replaced, the gross annual amount of CO2 as well as net amount of annual CO2 emissions mitigation potential considering CO2 emissions embodied in the manufacture of mixed-mode solar dryer has been estimated. The CO2 mitigation potential and amount of fossil fuels saved while drying potato samples were found to be the maximum for coal followed by light diesel oil and natural gas. It was inferred from the present study that by the year 2020, 23 % of CO2 emissions can be mitigated by the use of mixed-mode solar dryer for drying of agricultural products.

Drying experiments have been performed with potato cylinders and slices using a laboratory scale designed natural convection mixed-mode solar dryer. The drying data were fitted to eight different mathematical models to predict the drying kinetics, and the validity of these models were evaluated statistically through coefficient of determination (R(2)), root mean square error (RMSE) and reduced chi-square (χ (2)). The present investigation showed that amongst all the mathematical models studied, the Modified Page model was in good agreement with the experimental drying data for both potato cylinders and slices. A mathematical framework has been proposed to estimate the performance of the food dryer in terms of net CO2 emissions mitigation potential along with unit cost of CO2 mitigation arising because of replacement of different fossil fuels by renewable solar energy. For each fossil fuel replaced, the gross annual amount of CO2 as well as net amount of annual CO2 emissions mitigation potential considering CO2 emissions embodied in the manufacture of mixed-mode solar dryer has been estimated. The CO2 mitigation potential and amount of fossil fuels saved while drying potato samples were found to be the maximum for coal followed by light diesel oil and natural gas. It was inferred from the present study that by the year 2020, 23 % of CO2 emissions can be mitigated by the use of mixed-mode solar dryer for drying of agricultural products.

Environment-friendly treatment of sewage sludge has become tremendously important. Conversion of sewage sludge into energy products by environment-friendly conversion process, with its energy recovery and environmental benefits, is being paid significant attention. Direct liquefaction of sewage sludge into bio-oils with supercritical water (SCW) was therefore put forward in this study, as de-water usually requiring intensive energy input is not necessary in this direct liquefaction. Supercritical water may act as a strong solvent and also a reactant, as well as catalyst promoting reaction process. Experiments were carried out in a self designed high-pressure reaction system with varying operating conditions. Through orthogonal experiments, it was found that temperature and residence time dominated on bio-oil yield compared with other operating parameters. Temperature from 350 to 500°C and reaction residence time of 0, 30, 60min were accordingly investigated in details, respectively. Under supercritical conversion, the maximum bio-oil yield could achieve 39.73%, which was performed at 375°C and 0min reaction residence time. Meanwhile, function of supercritical water was concluded. Fuel property analysis showed the potential of bio-oil application as crude fuel.

Environment-friendly treatment of sewage sludge has become tremendously important. Conversion of sewage sludge into energy products by environment-friendly conversion process, with its energy recovery and environmental benefits, is being paid significant attention. Direct liquefaction of sewage sludge into bio-oils with supercritical water (SCW) was therefore put forward in this study, as de-water usually requiring intensive energy input is not necessary in this direct liquefaction. Supercritical water may act as a strong solvent and also a reactant, as well as catalyst promoting reaction process. Experiments were carried out in a self designed high-pressure reaction system with varying operating conditions. Through orthogonal experiments, it was found that temperature and residence time dominated on bio-oil yield compared with other operating parameters. Temperature from 350 to 500°C and reaction residence time of 0, 30, 60min were accordingly investigated in details, respectively. Under supercritical conversion, the maximum bio-oil yield could achieve 39.73%, which was performed at 375°C and 0min reaction residence time. Meanwhile, function of supercritical water was concluded. Fuel property analysis showed the potential of bio-oil application as crude fuel.

Abstract This study investigates the non-linear relationship between urbanization paths and CO2 emissions in selected South, South-East, and East Asian countries over the period 1971–2014. Based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework, we applied the advanced and robust methods of dynamic seemingly unrelated regression (DSUR), dynamic OLS (DOLS), and fully modified OLS (FMOLS) to estimate the long-term effects. The empirical findings revealed the inverted U-shaped effects of urbanization and urban agglomeration and the U-shaped impact of the largest city ratio on CO2 emissions. Urbanization and urban agglomerations improve environmental quality in the long-run and support ecological modernization theory. However, excessive concentration in the largest cities have severely affected the environmental quality and violates the notion of compact-city efficiencies. Moreover, energy intensity and economic growth positively affect CO2 emissions, while trade openness negatively influences CO2 emissions. Our robustness analysis at the country-level applies the augmented mean group (AMG) panel ARDL technique, which further supports the non-linear effect of urbanization paths on CO2 emissions except for a few countries. The results of the panel Granger non-causality approach unveil bidirectional causality of energy efficiency, economic growth, urbanization, and largest city ratio with CO2 emissions. In contrast, unidirectional causality runs from urban agglomeration to CO2 emissions. Our findings have important policy implications as we suggest green urban infrastructures, eco-friendly dwellings, smart cities, country-specific trade policies, and renewable energy options to improve the environmental quality.

Abstract This study investigates the non-linear relationship between urbanization paths and CO2 emissions in selected South, South-East, and East Asian countries over the period 1971–2014. Based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework, we applied the advanced and robust methods of dynamic seemingly unrelated regression (DSUR), dynamic OLS (DOLS), and fully modified OLS (FMOLS) to estimate the long-term effects. The empirical findings revealed the inverted U-shaped effects of urbanization and urban agglomeration and the U-shaped impact of the largest city ratio on CO2 emissions. Urbanization and urban agglomerations improve environmental quality in the long-run and support ecological modernization theory. However, excessive concentration in the largest cities have severely affected the environmental quality and violates the notion of compact-city efficiencies. Moreover, energy intensity and economic growth positively affect CO2 emissions, while trade openness negatively influences CO2 emissions. Our robustness analysis at the country-level applies the augmented mean group (AMG) panel ARDL technique, which further supports the non-linear effect of urbanization paths on CO2 emissions except for a few countries. The results of the panel Granger non-causality approach unveil bidirectional causality of energy efficiency, economic growth, urbanization, and largest city ratio with CO2 emissions. In contrast, unidirectional causality runs from urban agglomeration to CO2 emissions. Our findings have important policy implications as we suggest green urban infrastructures, eco-friendly dwellings, smart cities, country-specific trade policies, and renewable energy options to improve the environmental quality.

The battery power state (SOP) is the basic indicator for the Battery management system (BMS) of the battery energy storage system (BESS) to formulate control strategies. Although there have been many studies on state estimation of lithium-ion batteries (LIBs), aging and temperature variation are seldom considered in peak power prediction during the whole life of the battery. To fill this gap, this paper aims to propose an adaptive peak power prediction method for power lithium-ion batteries considering temperature and aging is proposed. First, the Thevenin equivalent circuit model is used to jointly estimate the state of charge (SOC) and SOP of the lithium-ion power battery, and the variable forgetting factor recursive least squares (VFF-RLS) algorithm and extended Kalman filter (EKF) are utilized to identify the battery parameters online. Then, multiple constraint parameters including current, voltage, and SOC were derived, considering the dependence of the polarization resistance of the battery on the battery current. Finally, the verification experiment was carried out with LiFePO4 battery. The experimental results under FUDS operating conditions show that the maximum SOC estimation error is 1.94%. And the power prediction errors at 20%, 50%, and 70% SOC were 5.0%, 8.1% and 4.5%, respectively. Our further work will focus on the joint estimation of battery state to further improve the accuracy.